How does Elastic Search work?

In times of constant rush, it is extremely important to quickly find information that interests us. Regardless of the topic, everyone wants an answer at their fingertips. Search is particularly important in the online environment and in the very process of creating IT tools. Regardless of the language in which the application is created, it usually has a huge amount of saved data. You need to search them to find the right ones. Therefore, the order of the steps performed and the very structure of the record are important. ElasticSearch is a facilitation for the entire search process. Check what exactly it is and why it’s good to use it!

How is data searched?

Before we focus on ElasticSearch itself, it is worth remembering how data is searched. In the case of full-text search of data contained in the application, we usually belong to the so-called smart search. Thanks to it, we are able to filter field values ​​and display items matching the query. It allows for minor errors occurring in the spelling of the search phrase, as well as to include variations of words that occur in almost every language.

In the case that there is not much data, the search engine built into the application (database engine) will be perfect. However, as the number of indexes that you need to search increases, you might want to use more advanced search solutions. One of them is ElasticSearch, which will support both the programmer creating the website and the end user, i.e. the client.

What is ElasticSearch?

As we have already mentioned, ElasticSearch is information retrieval software. Is a full-text search engine, and thus – a database using the Apache Lucene library. Thanks to this connection, it creates a powerful tool that allows comprehensive, real-time data searching. Therefore, it is not only a classic search, but also allows advanced grouping and filtering results according to specific guidelines.

ElasticSearch consists of a group of systems, including the Kibana Tool, Logstash Tool and the Beat Tool Family. Thanks to them, you can visualize data (also graphically), manage the process of adding system logs, add data of different origin, e.g. from text files, information on the operation of the website or related to packages sent over the network.

The main applications of ElasticSearch include full-text search, log collection and analysis, public data collection and analysis, measurement data collection and analysis, and data visualization.

How is ElasticSearch built?

To fully understand the possibilities of ElasticSearch, it is worth familiarizing yourself with its structure. Thanks to this, it is easier to understand its functioning and possibilities of use in its activities. Here are some basic concepts you use when using the tool.

Node – means a single server on which data searching and processing takes place. Each of these servers has its own unique name and port on which it operates. In standard it is port 9200.

Cluster – is a collection of one or several nodes.

Index – is a collection of documents with similar characteristics. Based on the index name, you can refer to specific collections of documents, delete or search for documents that are relevant at the moment. In standard relational databases, the index is considered a full-fledged database.

Type – a way of grouping data other than Index. It can also be called a table. However, its structure is not strictly defined, which distinguishes it from the tables contained in relational databases. The Type structure depends on the Documents stored in the specified group.

Document – these are records saved in JSON format.

What else is worth knowing about ElasticSearch? This is key information primarily for programmers. It is an Open Source project, which means it is free and there is no need to pay any fees for using the tool. So you can easily use the advanced search engine, which is constantly being developed. What’s more, many software allow for an intuitive connection with the ElasticSearch engine. So you can use it in working with Java, C # and Python.

When is ElasticSearch useful?

Both small and large sales platforms can use searches with ElasticSearch. A good example of proper use is the situation in which you have about 200,000 products and some programming experience.

We assume that we know what the SQL database query should look like. We also know that it should work properly, but also be fast and efficient so that the customer searching for a given product quickly reaches what he is interested in and does not change our store into a competitor’s store and its faster-running article search engine. We also remember that the query does not have to be only made up of the product name. It may also include, for example, the name of the manufacturer in its name. However, this makes things a little difficult for us. We need to decide which element of the query is more important, and which search element should have a greater impact on the final result displayed.

In this type of situation, thanks to ElasticSearch, you can add weight to each field and thus influence the scoring of the query. So you decide what is more important to you and what is more valuable for your client in terms of UX. You can do all this with very simple commands. And this is just one of the ElasticSearch functions that greatly simplifies the functioning of your store.

A correctly implemented ElasticSearch search engine provides extremely simple and pleasant operation of a website, application or e-commerce platform. For this reason, it enjoys growing popularity among programmers and internet business owners. Thanks to its flexibility and the ability to adapt the code to ElasticSearch, it is a tool worth using to achieve measurable results!